Description: Oracle Text uses standard SQL to index, search, and analyze text and documents stored in the Oracle database, in files, and on the web. Oracle Text can perform linguistic analysis on documents, as well as search text using a variety of strategies including keyword searching, context queries, Boolean operations, pattern matching, mixed thematic queries, HTML/XML section searching, and so on. It can render search results in various formats including unformatted text, HTML with term highlighting, and original document format. Oracle Text supports multiple languages and uses advanced relevance-ranking technology to improve search quality. Oracle Text also offers advanced features like classification, clustering, and support for information visualization metaphors. Platform: |
Size: 163840 |
Author:eranisrikantha |
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Description: Content-based medical image retrieval is now getting more and more attention in the
world, a feasible and efficient retrieving algorithm for clinical endoscopic images is urgently
required. Methods: Based on the study of single feature image retrieving techniques, including color
clustering, color texture and shape, a new retrieving method with multi-features fusion and relevance
feedback is proposed to retrieve the desired endoscopic images. Results: A prototype system is set
up to evaluate the proposed method’s performance and some evaluating parameters such as the
retrieval precision & recall, statistical average position of top 5 most similar image on various features, etc.
are therefore given. Conclusions: The algorithm with multi-features fusion and relevance feedback
gets more accurate and quicker retrieving capability than the one with single feature image retrieving
technique due to its flexible feature combination and interactive relevance feedback. Platform: |
Size: 359424 |
Author:gokul/goks |
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Search - relevance clustering